Bio
Dr. Vuda Sreenivasarao is a distinguished academic and researcher with a robust background in Computer Science and Engineering. He holds a Ph.D. in Computer Science and Engineering, along with an M.Tech in Computer Science and Engineering, an M.Phil in Mathematics, an M.Sc in Applied Mathematics, and a B.Sc in Mathematics, Physics, and Chemistry. Dr. Sreenivasarao has been affiliated with Singhania University and Bahir Dar University, contributing significantly to the fields of data mining, data warehousing, and machine learning. With 68 publications and over 350 citations, his work has made a notable impact. He has an h-index of 10 and an i10-index of 11. In addition to his research, Dr. Sreenivasarao has served as a reviewer for numerous journals and is a fellow of the Global Journal of Computer Science and Technology. His expertise spans database management, artificial intelligence, image processing, and pattern recognition.
Educational Journey
Singhania University
PhD(CSE), M Tech (CSE), M.Phil (Mathematics), M.Sc (A.O.Mathematics), B.Sc (MPC) • Computer Science and Engineering
Ph.D.
Experience
Editors Role
Reviewer
GJCST
2012 -Affiliations
Global Journal of Computer Science and Technology (GJCST)
Fellow
Member since 2013Grants and Awards
Fellow Membership
Global Journal of Computer Science and Technology (GJCST)
Research
Advanced Receiver Architectures in Radio-Frequency Applications
The general principles of several types of receivers fall under the two main headings of TRF (tuned radiofrequency) receivers, where the received signal is processed at the incoming frequency right up to the detector stage, and the superhet (supersonic heterodyne) receiver, where the incoming signal is translated (sometimes after some amplification at the incoming frequency) to an intermediate frequency for further processing. There are however, a number of variants of each of these two main types. Regeneration (‘reaction’ or ‘tickling’) may be applied in a TRF receiver, to increase both its sensitivity and selectivity. This may be carried to the stage where the RF amplifier actually oscillates – either continuously, so that the receiver operates as a synchrodyne or homodyne, or intermittently, so that the receiver operates as a super-regenerative receiver, both of which have been described previously. The synchrodyne or homodyne may be considered alternatively as a superhet, where the IF (intermediate frequency) is 0 Hz. In this paper we present the new type of receiver architectures which work in radiofrequencies.
Effect of Hot Forging on Chemical Composition and Metallographic Structure of Steel Alloys [Case Study on Din-100crmn6 Steel]
Massive defective products as a result of faulty heat- treatment process of a specific steel alloy, DIN 100CrMn6, are observed as a series issue. This is due to the remarkable market loss faced on the target industry of this research, Akaki Basic Metals Industry. The defective product of the stated steel alloy, mill grinding steel ball of cement industry, was observed and made reproduced its actual prototype using the same material and following the same production flow of the target industry. Three stages of the production flow were selected and the necessary tests, metallographic structure and the chemical composition, of the material were conducted at each selected process stages. The test stages adopted are; testing the raw material, the just as forged, and the heat treated final product. From the chemical composition and metallographic structure result of the first test stage, the mostly pearlite.
Improving Academic Performance of Students of Defence University Based on Data Warehousing and Data mining
The student academic performance in Defence University College is of great concern to the higher technical education managements, where several factors may affect the performance. The student academic performance in engineering during their first year at university is a turning point in their educational path and usually encroaches on their general point average in a decisive manner. The students evaluation factors like class quizzes mid and final exam assignment are studied. It is recommended that all these correlated information should be conveyed to the class teacher before the conduction of final exam. This study will help the teachers to reduce the drop out ratio to a significant level and improve the performance of students. Statistics plays an important role in assessment and evaluation of performance in academics of universities need to have extensive analysis capabilities of student achievement levels in order to make appropriate academic decisions. Academic decisions will result in academic performance changes, which need to be assessed periodically and over span of time. The performance parameters chosen can be viewed at the individual student, department, school and university levels. Data mining is used to extract meaning full information and to develop significant relationships among variables stored in large data set/ data warehouse. In this paper is an attempt to using concepts of data mining like k-Means clustering, Decision tree Techniques, to help in enhancing the quality of the higher technical educational system by evaluating student data to study the main attributes that may affect the performance of student in courses.
A Classification of Arial Data Based on Data Mining Clustering Algorithm
The Arial data contains date periodically observed with parameters of texture (min, max), flora, and density (min, max). The proposed Arial prediction system cluster and analyze, three input features that is average texture, flora, average density according to number of days to predict Arial for Surveillance applications. The proposed system realizes the k-means clustering algorithm for grouping similar features based on user intended period, further the system analyze using PCA (Principal Component Analysis) on same data.
